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jupyter/体测单位/燕山石化.ipynb
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2023-04-24 10:20:14 +00:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "bf152e7d-6a36-4877-98d9-f11e3a73792e",
"metadata": {},
"source": [
"## 导入人员信息"
]
},
{
"cell_type": "code",
"execution_count": 106,
"id": "1b92b7c5-cb77-49da-95b7-34827ecf1d16",
"metadata": {
"execution": {
"iopub.execute_input": "2023-04-24T10:05:01.926272Z",
"iopub.status.busy": "2023-04-24T10:05:01.925417Z",
"iopub.status.idle": "2023-04-24T10:05:04.468748Z",
"shell.execute_reply": "2023-04-24T10:05:04.467687Z",
"shell.execute_reply.started": "2023-04-24T10:05:01.926232Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"source": [
"import openpyxl\n",
"import json\n",
"\n",
"\n",
"wb = openpyxl.load_workbook('data/燕山石化人员情况表.xlsx')\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" if sheet.cell(n,1).value is not None:\n",
" code = int(sheet.cell(n, 1).value)\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 2).value \n",
" dict1['sex'] = sheet.cell(n, 3).value\n",
" birth = str(sheet.cell(n, 6).value).split()[0]\n",
" dict1['birth'] = birth\n",
" if sheet.cell(n,5).value is not None:\n",
" dict1['phone'] = sheet.cell(n, 5).value\n",
" if sheet.cell(n,7).value is not None:\n",
" dict1['id_num'] = sheet.cell(n, 7).value\n",
" if sheet.cell(n,8).value is not None:\n",
" dict1['SAP'] = sheet.cell(n, 8).value\n",
" if sheet.cell(n,9).value is not None:\n",
" dict1['工作单位'] = sheet.cell(n, 9).value\n",
" if sheet.cell(n,10).value is not None:\n",
" dict1['车间'] = sheet.cell(n, 10).value\n",
" else:\n",
" dict1['车间'] =''\n",
" if sheet.cell(n,11).value is not None:\n",
" dict1['班组'] = sheet.cell(n, 11).value\n",
" else:\n",
" dict1['班组'] =''\n",
" if sheet.cell(n,12).value is not None:\n",
" dict1['工作性质'] = sheet.cell(n, 11).value\n",
" person[code] = dict1\n",
"filename = 'data/燕山石化人员名单.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "f5c73dff-697d-4ba5-a90c-9bed68eaf4b3",
"metadata": {},
"source": [
"## 每日成绩导入"
]
},
{
"cell_type": "code",
"execution_count": 107,
"id": "71e1ec6a-6797-4496-969a-1d1461b9ea58",
"metadata": {
"execution": {
"iopub.execute_input": "2023-04-24T10:06:37.571983Z",
"iopub.status.busy": "2023-04-24T10:06:37.571077Z",
"iopub.status.idle": "2023-04-24T10:06:37.786825Z",
"shell.execute_reply": "2023-04-24T10:06:37.785861Z",
"shell.execute_reply.started": "2023-04-24T10:06:37.571941Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"423\n",
"5593 刘安全 已测试!\n",
"423\n",
"2645\n"
]
}
],
"source": [
"import json\n",
"import time\n",
"import csv\n",
"\n",
"filename = '../item.json'\n",
"item = {}\n",
"unit = {}\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"for k,v in dict1.items():\n",
" item[k] = v\n",
"re_ta = {}\n",
"dict1 = {}\n",
"list1 = []\n",
"filename = 'data/燕山石化人员名单.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"filename = 'data/places_result_20230424.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n",
" for line in fl:\n",
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
" list1.append(line)\n",
"#print(list1)\n",
"for result in list1:\n",
" user = str(result[2])\n",
" if user in dict1.keys(): \n",
" m_item = str(result[3]) \n",
" re_ta.setdefault(user,{}) \n",
" re_ta[user]['name'] = dict1[user]['name']\n",
" re_ta[user]['sex'] = dict1[user]['sex'] \n",
" re_ta[user]['部门'] = dict1[user]['工作单位']\n",
" item_name = item[m_item]['name']\n",
" re_ta[user].setdefault(item_name,{}) \n",
" score = int(result[4])/item[m_item]['divisor'] \n",
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
"print(len(re_ta))\n",
"filename = 'data/result_燕山石化.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
"for k in re_ta.keys():\n",
" if k in dict2.keys():\n",
" print(k,dict2[k]['name'],'已测试!')\n",
"for k, v in re_ta.items():\n",
" if k not in dict2.keys():\n",
" dict2[k] = v\n",
" else:\n",
" for k1,v1 in v.items():\n",
" dict2[k][k1] = v1\n",
"filename = 'data/result_燕山石化(20230424).json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(re_ta, fl, ensure_ascii=False) \n",
"print(len(re_ta))\n",
"filename = 'data/result_燕山石化.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2, fl, ensure_ascii=False) \n",
"print(len(dict2))"
]
},
{
"cell_type": "markdown",
"id": "79147ba8-4b90-40ba-81a9-e6062600c239",
"metadata": {},
"source": [
"## 每日成绩导出"
]
},
{
"cell_type": "code",
"execution_count": 108,
"id": "c24880ad-bbbd-4ad8-a894-cbcea389e822",
"metadata": {
"execution": {
"iopub.execute_input": "2023-04-24T10:08:16.575368Z",
"iopub.status.busy": "2023-04-24T10:08:16.574601Z",
"iopub.status.idle": "2023-04-24T10:08:16.751333Z",
"shell.execute_reply": "2023-04-24T10:08:16.750617Z",
"shell.execute_reply.started": "2023-04-24T10:08:16.575338Z"
},
"tags": []
},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
"title = ['编号','姓名','性别','单位','车间','班组','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
"filename = 'data/result_燕山石化(20230424).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/燕山石化人员名单.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
" \n",
"list1 = []\n",
"for k, v in dict1.items():\n",
" list2 = []\n",
" list2.append(str(k).rjust(5,'0'))\n",
" list2.append(v['name']) \n",
" list2.append(dict2[k]['sex'])\n",
" list2.append(dict2[k]['工作单位']) \n",
" list2.append(dict2[k]['车间'])\n",
" list2.append(dict2[k]['班组'])\n",
" for item in items:\n",
" if item in v.keys():\n",
" list2.append(v[item]['成绩']) \n",
" elif item =='name':\n",
" list2.append(v[item])\n",
" else:\n",
" list2.append('') \n",
" list1.append(list2)\n",
"filename = 'data/燕山石化体测情况表(20230424).xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
"for row in list1:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename)"
]
},
{
"cell_type": "markdown",
"id": "6d431fc1-b743-467c-91b3-9788e245becb",
"metadata": {},
"source": [
"## 统计部门测试人数"
]
},
{
"cell_type": "code",
"execution_count": 109,
"id": "68454877-f1fe-4eed-8a48-265e428f892e",
"metadata": {
"execution": {
"iopub.execute_input": "2023-04-24T10:08:30.444506Z",
"iopub.status.busy": "2023-04-24T10:08:30.444058Z",
"iopub.status.idle": "2023-04-24T10:08:30.475858Z",
"shell.execute_reply": "2023-04-24T10:08:30.474801Z",
"shell.execute_reply.started": "2023-04-24T10:08:30.444476Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'行政事务中心(离退中心)工会': 8, '热电厂工会': 1, '化学品厂工会': 55, '高科公司工会': 102, '炼油厂工会': 51, '有机化工厂工会': 131, '检验计量中心工会': 32, '物装中心工会': 2, '生产运行保障中心': 2, '烯烃厂工会': 6, '机关工会': 8, '合成树脂厂': 14, '消防中心工会': 2, '合成橡胶厂工会': 8, '储运厂工会': 1}\n"
]
}
],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"filename = 'data/result_燕山石化(20230424).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"dict2 = {}\n",
"for k, v in dict1.items():\n",
" unit = v['部门']\n",
" dict2.setdefault(unit,0)\n",
" dict2[unit] = dict2[unit] + 1\n",
"print(dict2)\n",
"title =['单位','体测人数']\n",
"list1 = [] \n",
"for k, v in dict2.items():\n",
" list2 = []\n",
" list2 = [k,v]\n",
" list1.append(list2)\n",
"filename = 'data/燕山石化部门测试人数情况表(20230424).xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
"for row in list1:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename)"
]
},
{
"cell_type": "markdown",
"id": "8becc0af-d22b-46a2-b35e-9122942515d4",
"metadata": {},
"source": [
"## 每日未测试人员情况表"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "7085bf6f-7465-44fb-bddb-38130fbe5618",
"metadata": {
"execution": {
"iopub.execute_input": "2023-04-17T12:58:45.236098Z",
"iopub.status.busy": "2023-04-17T12:58:45.235274Z",
"iopub.status.idle": "2023-04-17T12:58:46.270936Z",
"shell.execute_reply": "2023-04-17T12:58:46.270191Z",
"shell.execute_reply.started": "2023-04-17T12:58:45.236059Z"
},
"tags": []
},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"title = ['编号','姓名','性别','单位','车间','班组']\n",
"filename = 'data/result_燕山石化(20230417).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/燕山石化人员名单.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
"list1 = []\n",
"for k, v in dict2.items():\n",
" list2 = []\n",
" if k not in dict1.keys():\n",
" list2.append(str(k).rjust(5,'0'))\n",
" list2.append(v['name']) \n",
" list2.append(dict2[k]['sex'])\n",
" list2.append(dict2[k]['工作单位']) \n",
" list2.append(dict2[k]['车间'])\n",
" list2.append(dict2[k]['班组'])\n",
" list1.append(list2)\n",
"filename = 'data/燕山石化未体测人员名单(20230417).xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
"for row in list1:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename) "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6e1dda56-541b-4afe-8ae7-2a8dd7ec5eac",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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"nbformat": 4,
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}